Think your business is too small to be a target of a cyber attack? Think again. Most cyber-attacks occur against
small and mid-size businesses. Here are just a few of the scary stats:
Worse yet, cybercriminals are continually leveraging new tactics and technology to evade traditional, rule-based email security solutions and static AI phishing detection tools. These tactics not only increase phishing threats but also create a lot of distraction for the security teams remediating the threats.
To address the next generation of phishing, small businesses need to leverage adaptive AI technology. Adaptive AI is a technology that learns, adapts, and improves with changes in the environment. Essentially, it evolves with the threat landscape to respond to new email attacks quickly.
3 Questions To Ask When Evaluating Email Security Solutions
Does your solution automatically respond to new data and adapt to email threats?
Static AI solutions typically can’t respond to new data or adapt to emerging threats because they are trained on yesterday’s data and on predefined models and tend to be single-purposed. They can tackle a specific use case, like building social graphs, and analyze the content to identify and flag language often used in phishing attacks. While this can effectively detect known unknowns, it allows new attacks to go undetected–increasing the risks of a successful phishing campaign.
Solutions that leverage adaptive AI (CM3 deploys IRONSCALES for this) are more multi-purpose in nature. Not only can they build social graphs and analyze behavior and the intent of the content, but they are also self-learning and continuously adapting to new threats by analyzing and training on real-time data to detect and remediate emerging threats.
Can your system adjust its behavior based on user feedback and the security team decisions and insights?
Human feedback is a critical contributor to reinforcing the machine learning model. When a new threat slips past detection, the reliance on human reporting of suspicious emails or flagging false positives can retrain the AI model to look for similar threats.
Static AI solutions typically don’t adjust their behavior on real-time user feedback or human insights. Since they operate based on historical data, any missed threats or false positives involve a long cycle of escalation to the vendor for review, approval, and adjustments.
How does your solution handle zero-day threats?
A zero-day threat is an unknown vulnerability in your computer or mobile device’s software or hardware. Adaptive AI solutions utilize a combination of advanced machine learning techniques, anomaly detection algorithms, behavioral and content analysis, and human insights to identify suspicious patterns that indicate potential zero-day threats. Once these threats are identified and insights from credible threat hunters are gathered, the models recalibrate to detect and remove similar threats automatically.
Content for this blog was provided by IRONSCALES. CM3 proudly deploys the IRONSCALES email security solution.